Applying function with multiple arguments to create a new pandas column

Question

I want to create a new column in a pandas data frame by applying a function to two existing columns  Following this answer I ve been able to create a new column when I only need one column as an argument   import pandas as pd df   pd DataFrame   A    10 20 30    B    20  30  10     def fx x       return x   x  print df  df  newcolumn     df A apply fx  print df    However  I cannot figure out how to do the same thing when the function requires multiple arguments  For example  how do I create a new column by passing column A and column B to the function below   def fxy x  y       return x   y

User · Answer

If you need to create multiple columns at once    Create the dataframe   import pandas as pd df   pd DataFrame   A    10 20 30    B    20  30  10     Create the function   def fab row                                                         return row  A     row  B    row  A     row  B    Assign the new columns   df  newcolumn    df  newcolumn2     zip  df apply fab  axis 1

User · Answer

Alternatively  you can use numpy underlying function    gt  gt  gt  import numpy as np  gt  gt  gt  df   pd DataFrame   A    10 20 30    B    20  30  10     gt  gt  gt  df  new column     np multiply df  A    df  B     gt  gt  gt  df     A   B  new column 0  10  20         200 1  20  30         600 2  30  10         300   or vectorize arbitrary function in general case    gt  gt  gt  def fx x  y           return x y      gt  gt  gt  df  new column     np vectorize fx  df  A    df  B     gt  gt  gt  df     A   B  new column 0  10  20         200 1  20  30         600 2  30  10         300

User · Answer

You can go with  greenAfrican example  if it s possible for you to rewrite your function  But if you don t want to rewrite your function  you can wrap it into anonymous function inside apply  like this    gt  gt  gt  def fxy x  y           return x   y   gt  gt  gt  df  newcolumn     df apply lambda x  fxy x  A    x  B     axis 1   gt  gt  gt  df     A   B  newcolumn 0  10  20        200 1  20  30        600 2  30  10        300

User · Answer

One more dict style clean syntax   df  new column     df apply lambda x  x  A     x  B    axis   1    or   df  new column     df  A     df  B

User · Answer

This solves the problem   df  newcolumn     df A   df B   You could also do   def fab row     return row  A     row  B    df  newcolumn     df apply fab  axis 1

[python] Applying function with multiple arguments to create a new pandas column

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